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An integrated bi-objective U-shaped assembly line balancing and parts feeding problem: optimization model and exact solution method

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ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE 2022年第7-9期90卷 679-696页

作者： Yilmaz, Omer Faruk Karadeniz Tech Univ Dept Ind Engn TR-61080 Trabzon Turkey

In this study, an integrated bi-objective objective U-shaped assembly line balancing and parts feeding problem is explored by considering the heterogeneity inherent of workers. An optimization model is developed to formulate the addressed problem. Since the problem includes two different objectives, namely the minimizing the operational cost and maximum workload imbalance, the Pareto-optimal solutions are found by employing the second version of the augmented epsilon-constrained (AUGMECON2) method. To investigate the impact of qualification of workers on the system performance, a set of scenarios is constructed based on the worker skill levels. Each scenario is determined based on the nature of the worker pool in which workers are assigned to the stations. The optimization model and implemented method are validated through data taken from water-meter and elevator producers. The computational results reveal that the scenarios have a great impact on system performance. In particular, it is revealed that as the skill levels of workers increases, the quality of the Pareto-optimal solutions increase by up to 30% in terms of the comparison metrics. Therefore, an order release mechanism and worker training activities are suggested to be performed to enhance system performance.

关键词： U-shaped assembly line balancing problem Parts feeding problem bi-objective optimization model AUGMECON2 method

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Inbound logistics optimization for fresh oranges with waste management

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JOURNAL OF FOOD ENGINEERING 2025年 391卷

作者： Anwar, Kiran Turkay, Metin Koc Univ Rumelifeneri Yolu TR-34450 Istanbul Turkiye

Typical fruit supply chains include several echelons such as farms, primary fruits-processing-facilities to produce main products, secondary fruits-processing-facilities to produce by-products, distribution centers, retailers, and consumers. This paper focuses on the inbound logistics operations that cover the logistics planning for transporting the fruits collected at the farms to the primary fruit processing facilities. Fruit supply chains are considered difficult to manage due the perishable nature of fruits and time constraints to avoid contamination and wastage. The objective of this research is to optimize inbound logistics in fruit supply chains by developing an optimization model that minimizes fruit losses during transportation and identifies optimal waste management practices. This approach not only reduces waste but also lowers greenhouse gas (GHG) emissions associated with fruit wastage. A bi-objective optimization model for the inbound logistics of fresh fruits is presented;the first objective is to minimize the total cost considering the environmental sustainability factors and the second objective is to minimize the carbon footprint and GHG emissions. Fresh fruit losses and wastage caused by changes in temperature, shelf life, and total time spent on transportation during inbound logistics is quantified. The model is applied to original data of fresh Valencia oranges harvested from farms in Egypt and computational results indicate that the fruit loss per month is decreased from 29% to less than 2% during the inbound logistics operations. Three methods are used to solve the bi-objective optimization problem, and the results are compared.

关键词： bi-objective optimization model Mixed-integer linear programming Fresh fruit waste management Pareto optimal solutions Logistics planning

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bi-objective optimization modeling of a three-level supply chain in production planning and scheduling considering price-dependent demand: a case study of a soap factory

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RAIRO-OPERATIONS RESEARCH 2024年第6期58卷 4997-5028页

作者： Eslami, Reyhaneh Abedini, Mehran Zokaee, Mahsa Rabbani, Masoud Aghsami, Amir Univ Tehran Coll Engn Sch Ind & Syst Engn Tehran Iran Univ Toronto Dept Mech & Ind Engn 5 Kings Coll Rd Toronto ON M5S 3G8 Canada Ankara Yildirim Beyazit Univ Dept Ind Engn Ankara Turkiye

Effective competition in the manufacturing industry requires careful planning and scheduling of production activities, commonly referred to as production planning and scheduling (PPAS). Furthermore, today, all organizations are striving to preserve the environment and improve the climate by reducing greenhouse gas emissions. This study presents a bi-objective mathematical model for a three-level supply chain. The primary objective of the model is to maximize profit, while the secondary objective is to minimize greenhouse gas emissions. By adopting this model, companies can strive towards achieving their business goals while simultaneously contributing to a sustainable future. Numerical experiments demonstrate the applicability of the developed model, and a case study in a soap factory is presented to calculate the optimal production quantities and determine the best price to increase demand while achieving profit. Finally, by conducting sensitivity analysis, optimal strategic decisions and useful management insights have been identified. According to the results and examination of the experiments, expanding the capacity and production rate, especially when the market potential for buying products is higher, fulfills the main goals. Also, in times of market recession, the variety of quality and price of products will lead to more profit.

关键词： Production planning and scheduling three-level supply chain environmental issues price dependent demand bi-objective optimization model

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Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) optimization

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JOURNAL OF MARINE SCIENCE AND ENGINEERING 2025年第4期13卷 752-752页

作者： Yang, Haiying Ren, Feiyang Yin, Jingbo Wang, Siqi Khan, Rafi Ullah Shanghai Jiao Tong Univ Sch Ocean & Civil Engn Dept Transportat Engn State Key Lab Ocean Engn Shanghai 200240 Peoples R China COSCO Shipping Technol Co Ltd Shanghai 200135 Peoples R China

In response to growing environmental concerns and regulatory pressures, reducing carbon emissions in maritime transport has become a priority. Shipping companies face the challenge of balancing profitability objectives with the imperative to minimize their environmental footprint. This study addresses the tramp ship routing and scheduling problem by incorporating the carbon intensity indicator (CII) into the optimization framework. A bi-objective optimization model is developed, with two objective functions aimed at maximizing fleet profit and improving CII ratings. The Gale-Shapley algorithm is employed to achieve stable vessel-cargo matching, and the genetic algorithm is adopted for iterative optimization. This computational study, based on real historical data, verifies the effectiveness of the proposed model and algorithm. The results demonstrate notable improvements in fleet efficiency and environmental performance, increasing profitability by 4.38% while maintaining favorable CII ratings. The findings provide valuable theoretical guidance for shipping companies navigating increasingly stringent CII regulations.

关键词： tramp ship routing and scheduling carbon intensity indicator bi-objective optimization model Gale-Shapley algorithm genetic algorithm

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Integrated temporary facility location and casualty allocation planning for post-disaster humanitarian medical service

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2019年 128卷 1-16页

作者： Liu, Yang Cui, Na Zhang, Jianghua Shandong Univ Sch Management Jinan 250100 Shandong Peoples R China Univ Jinan Sch Civil Engn & Architecture Jinan 250022 Shandong Peoples R China

The planning of temporary medical service facility location and the distribution of casualties to these facilities require to consider casualty triage, health deterioration conditions, and equitable distribution of limited medical resources. The paper develops a bi-objective optimization model to determine the optimal temporary medical service locations and medical service allocation plan by maximizing the number of expected survivals and minimizing the total operational cost in the way of using ambulances and helicopters. Based on a-constraint method, we propose an iteration method to obtain the Pareto front of the bi-objective optimization model. Sensitivity analyses are conducted to provide helpful managerial insights.

关键词： Humanitarian medical service Ambulances and helicopters Location problem bi-objective optimization model

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Capacity Design and Pareto Improvement of Highway Toll Plaza in a Competitive Transport System

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IEEE ACCESS 2021年 9卷 113642-113652页

作者： Yong, Gui Zhang, Jing Su, Nuoer Feng, Xueke Inner Mongolia Univ Finance & Econ Sch Math & Stat Hohhot 010070 Peoples R China Inner Mongolia Key Lab Econ Data Anal & Min Hohhot 010070 Peoples R China

As the traffic infrastructure for collecting vehicle tolls, the capacity of the toll plaza determines the service level of the entire highway. The capacity of a toll plaza is highly correlated with its operating costs, especially in peak periods. In this paper, it is assumed that in a competitive transportation system, the residential area and the workplace are connected by a highway with a toll plaza which forms a bottleneck, parallel to a mass transit line;commuters can choose to travel by car or by public transport. By establishing an equilibrium model and two mathematical programming models, the capacity designs of the toll plaza were studied during the traffic service period to achieve three objectives, namely, the toll plaza breaking even, profit maximization, and total social cost minimization of the transportation system. The travel modal splits were analyzed under travel equilibrium in three situations, respectively. In addition, a bi-objective optimization model was developed to optimize total profit and total social cost, and a Pareto optimization scheme was analyzed. Finally, the theoretical analyses were also verified by numerical examples.

关键词： Road transportation Pricing Licenses Roads Maintenance engineering Analytical models Vehicles bi-modal traffic bi-objective optimization model capacity design highway toll plaza

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A hybrid approach for designing a railway transportation network of hazardous material tanks

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APPLIED MATHEMATICAL modelLING 2022年 110卷 112-130页

作者： Zhang, Lukai Wang, Yingping Zhang, Peng Minist Transport Transport Planning & Res Inst Chaoyang Dist Beijing 100029 Peoples R China Lab Traff & Transport Planning Digitalizat Chaoyang Dist Beijing 100029 Peoples R China

This research proposes a design approach by hybrid optimization, which mainly includes the qualitative assessment and quantitative planning. In view of the multiple qualitative indicators in the location of tank handling stations, the fuzzy calibration is used to determine the ranking index of each candidate station. After that, these indices are integrated into the optimization model of a transportation network as weights. This bi-objective model is to minimize the total risk and the total operating cost. In order to verify the validity of the 0-1 quadratic programming model and the discrete characteristics of solution space, we propose a numerical algorithm. The process of the numerical algorithm is based on linearization conversion and the parallel branch & bound. For large-scale cases with a mass of variables and constraints, a heuristic is made, namely Pareto shuffled frog leaping algorithm. A case study is completed in the railway freight network in north China. This research can provide a theoretical basis and operating reference for railway transportation of hazardous materials.

关键词： Transportation network design Fuzzy calibration bi-objective optimization model Pareto shuffled frog leaping algorithm

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A data-driven optimization approach to improving maritime transport efficiency

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2024年 180卷

作者： Yan, Ran Liu, Yan Wang, Shuaian Nanyang Technol Univ Sch Civil & Environm Engn 50 Nanyang Ave Singapore Singapore Hong Kong Polytech Univ Fac Business Hung Hom Kowloon Hong Kong 999077 Peoples R China

Ship inspections conducted by port state control (PSC) can effectively reduce maritime risks and protect the marine environment. The effectiveness of PSC depends on accurately selecting ships with higher risk for inspection. Ship risk profile (SRP) is currently the most common method of quantifying ship risk, but the thresholds of the factors that determine a ship's risk and classification in the SRP framework are subjective and can make the ship selection process less efficient. In this study we propose a data -driven bi-objective nonlinear programming model, referred to as the SRP+ model, to optimize the thresholds in the original SRP framework. To solve the model, we first linearize the nonlinear optimization model using the big -M method, and then develop an augmented epsilon -constraint method to transform the bi-objective model to a single -objective model and obtain all Pareto optimal solutions. We also conduct a case study using real PSC inspection records at the Hong Kong port to construct and validate the SRP+ model. The results suggest that the threshold of the total weighting points to classify a ship as high -risk ship should be slightly increased, the thresholds of ship age should be significantly increased, the threshold of historical deficiency number should be increased, while the threshold of historical ship detention times should be decreased. The proposed SRP+ model can benefit both conservative and open-minded port authority decision makers by identifying ships with more deficiencies and/or higher detention probability more efficiently. The model can also be applied to other risk management problems in transportation and supply chain management, in addition to the maritime transport domain.

关键词： Maritime transport Data-driven optimization bi-objective optimization model Predictive analytics Threshold optimization

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Urban water supply system optimization and planning: bi-objective optimization and system dynamics methods

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COMPUTERS & INDUSTRIAL ENGINEERING 2020年 142卷 106373-106373页

作者： Xu, Zhongwen Yao, Liming Chen, Xudong Sichuan Univ Business Sch Chengdu 610064 Peoples R China Sichuan Univ State Key Lab Hydraul & Mt River Engn Chengdu 610064 Peoples R China Chengdu Univ Technol Coll Management Sci Chengdu 610059 Peoples R China

Sustainable, low-cost, environmentally conscious development is a major challenge for urban water supply systems. This study considers household and industrial water demand and establishes a bi-objective model to balance the economic and environmental cost of a three-stage urban water supply system including water production, distribution, and treatment processes. Considering different attitudes toward the increasing imbalance between water demand and supply, three hypothetical scenarios are designed based on which three sets of data on water demand and wastewater production volumes are defined. Then, a two-step method is applied to obtain solutions to decision variables (potable water use rate and wastewater untreated rate). After optimization, a system dynamics model is applied to test water supply system performance under short-, medium-, and longterm planning scenarios. Finally, the model is applied to Singapore to test its feasibility. The proposed bi-objective model provides managerial insights into the use of alternative water resources. For example, in 2020, water demand is simulated as 5.63 x 10(8)m(3). After optimization using the proposed model, the quantity of alternative water is 2.5 x 10(8)m(3) (water from the local catchment), 2.5 x 10(8)m(3) (imported water), 5.31 x 10(7)m(3) (desalinated water), 4.05 x 10(7)m(3) (NEWater for indirect potable use), and 8.10 x 10(7)m(3) (NEWater for direct nonpotable use). Total water supply is 6.75 x 10(8)m(3) , which means there is some redundancy in water supply. Further, three indexes-supply-demand ratio, economic cost, and environmental cost-help to identify the suitable planning period: the medium-term focus is the most appropriate option as it promises water adequacy for over 15 years and has lower energy costs and less negative environmental impact during the evaluation years. In addition, this study proves the influence of decision makers' preferences on contradictory objective functions (economic cost minimi

关键词： Urban water supply system System dynamics model bi-objective optimization model

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Metro train delay-recovery strategy considering passenger waiting time and energy consumption: a real-world case study

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INTERNATIONAL JOURNAL OF RAIL TRANSPORTATION 2024年第1期12卷 76-101页

作者： Li, Wenxin Zhong, Qingwei Peng, Qiyuan Liu, Jing Ma, Chao Hubei Univ Arts & Sci Hubei Key Lab Power Syst Design & Test Elect Vehi Xiangyang Peoples R China Civil Aviat Flight Univ China Coll Air Traff Management Guanghan 618307 Peoples R China Southwest Jiaotong Univ Sch Transportat & Logist Chengdu Peoples R China Southwest Jiaotong Univ Natl United Engn Lab Integrated & Intelligent Tra Chengdu Peoples R China

Based on actual delay-recovery strategies (ADRS) on site only considers reducing the delays and ignores the operation cost of the enterprise. This study proposes optimized delay-recovery strategies (ODRS) to reduce the impact of delay on passengers and increase energy efficiency simultaneously. A bi-objective optimization model is used to deal with different initial delay scenarios and minimize the additional waiting time of passengers (AWTP) and total energy consumption (TEC). In the solving process, the non-dominated sorting genetic algorithm-II (NSGA-II) is used to solve the models, which can get the effective Pareto frontier solutions. Finally, Chengdu Metro is taken as the numerical experiments to verify the performance of the models. The results show that the ODRS can effectively reduce the AWTP and TEC than the ADRS. Furthermore, with the increase of initial delay time, the optimization effect of ODRS will be more obvious.

关键词： Metro system delay-recovery energy consumption bi-objective optimization model energy-saving driving control

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